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NONUNIFORM COURSE OF ACUTE PERIOD OF HEMORRHAGIC STROKE: ANALYSIS USING METHODS OF MULTIVARIATE STATISTICS

Journal: NAUKA MOLODYKH (Eruditio Juvenium) (Vol.9, No. 1)

Publication Date:

Authors : ;

Page : 59-67

Keywords : hemorrhagic stroke; Glasgow coma scale; NHISS; logit regression analysis; С&RT analysis k-means; cluster analysis; discriminant function;

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Abstract

Background. Hemorrhagic stroke is an important medical and social problem both in the world and in the Russian Federation due to high parameters of morbidity, mortality and disability. Aim. To compare expert assessments and formalized multivariate statistical procedures in analysis of clinical inhomogeneity of patients with intracranial hematoma of supratentorial location. Materials and Methods. 75 Patients who took treatment in the neurovascular department of Ryazan Regional Clinical Hospital with the diagnosis of hemorrhagic stroke, were examined. Of them, there were 40 men and 35 women with the mean age 68.1 years. Results. Primarily, on the basis of expert assessments, the patients were divided to 2 groups: with unfavorable course and with relatively favorable course – satisfactory condition, regress of symptoms, recovery of the level of consciousness. In the first stage, in result of the primary expert assessment, the patients were divided to subgroups with favorable and unfavorable course. After that, significant for selection of groups variables were used in selection of clusters: method of hierarchial tree for determination of the number of groups; k-means method for identification of their elements. Discrimination analysis was used for selection of variables in NIHSS and GCS, and also for assessment of canonical correlations. After that, cluster analysis of NIHSS and GCS dynamics was conducted on the 1st, 3rd, 21st day for selection of groups in high-dimensional space of signs with exclusion of subjective expert assessments. Three main groups of patients were selected. In the second stage, in accordance with the number of groups, patients belonging to the corresponding clusters were identified using the k-means method. Cluster 1 included patients with a poor prognosis, clusters 2 and 3 suggested a more favorable course of the acute period with worse parameters in cluster 2. Conclusions. Use of discriminant functions confirms the role of severity of depression of consciousness and of the volume of hematoma in the unfavorable course.

Last modified: 2021-04-05 23:24:22